ScholarWorks@SOONCHUNHYANG UNIVERSITY: Woo, Ji young

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Woo, Ji young (우지영)

College of Software Convergence (Department of Ai and Big Data)

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machine learning:9||deep learning:8||Deep learning:6||Predictive models:5||Data models:4||Monitoring:4||convolutional neural network:4||byte stream:3||Internet of Things:3||Artificial intelligence:2||malware:2||Machine learning:2||malware detection:2||social media:2||Transformers:2||Analytical models:2||Object detection:2||Type 2 diabetes:2||Driving data:2||natural language processing:2||text mining:2||Sensor systems:2||Feature extraction:2||continuous glucose monitoring:2||online game:2||Generative adversarial network:2||Diffusion model:2||Internet of Things (IoT) platform:2||Multiagent reinforcement learning:2||detection:2||MMORPG:2||Accuracy:2||big data:2||Effect on Retweeting:1||Electrocardiography:1||Electroencephalography:1||Emotion recognition:1||Ensemble method:1||Error grid analysis:1||Fast Healthcare Interoperability Resources (FHIRs):1||Feature selection:1||Forecasting:1||Games:1||Glucose:1||Graph neural networks:1||HWP:1||HWP file:1||Hangul Word Processor:1||Hangul word processor:1||Healthrelated data:1||HeuristicSystematic Model (HSM) of information processing:1||Hierarchical clustering:1||Hospitals:1||Hybrid electric vehicle:1||Hybrid model:1||Image processing:1||Invehicle network:1||Intelligent sensors:1||Intrusion detection:1||IoT platform:1||LoRa networks:1||MIMICs:1||MMORPG user behavior:1||Machine learning algorithms:1||Machine vision:1||Malware:1||Malware Detection:1||Malware detection:1||Medical imaging:1||Medical services:1||Mileage:1||Moving direction:1||Multitask learning:1||Mutual information:1||Neural Networks:1||Numerical models:1||OBDII:1||Object tracking:1||Online games:1||PDF:1||PM2:1||Particulate matter:1||Passive infrared:1||Pedestrian:1||Pediatrics:1||People counting:1||Portable document format:1||Process inspection:1||Profanity:1||Pyroelectric infrared (PIR) sensor:1||Radio frequency:1||Reinforcement learning:1||Respiratory system:1||Sensor data augmentation:1||Sensors:1||Shapley additive explanations values:1||Smart phones:1||Smart traffic safety sign:1||Social factors:1||Source credibility:1||Stacking:1||Standards:1||Support vector machines:1||Task analysis:1||Theory and Information Entropy:1||Training:1||Transfer learning:1||Transformer:1||Twitter:1||Twitter user profile:1||Understanding the Uncertainty:1||User experience:1||Vehicles:1||Vision transformer models:1||White blood cell:1||White blood cell classification:1||White blood cell detection:1||Wire harness:1||activitypatterns:1||adversarial attack:1||albuminuria:1||allcause mortality:1||anesthesia:1||arterial hypotension:1||biomedical sensor:1||cardiovascular mortality:1||characteristics change analysis:1||chronic kidney disease:1||churn prediction:1||churn user prediction:1||cluster analysis:1||cohort monitoring:1||content noise:1||convolutional neural networks:1||corporate financial performance:1||data mining:1||diabetic inpatient:1||digital twin:1||driver emotion detection:1||driving data:1||end stage renal disease:1||ensemble model:1||environmental social and governance (ESG) news sentiment analysis:1||estimation:1||evaluating churn prediction model:1||everyday life:1||feature engineering:1||feature selection:1||game bot:1||gamebased learning:1||gamification:1||gender classification:1||glucose prediction model:1||gold farming group:1||graph neural networks:1||higher education:1||hybrid electric vehicle (HEV):1||hyperglycemia:1||hypoglycemia:1||hypotension:1||hypotension prediction:1||industryspecific ESG strategies:1||information security incident:1||information security policy:1||interoperability:1||invasive blood pressure:1||java script:1||lifelog:1||lowgrade albuminuria:1||machine learning algorithm:1||machine learning model:1||machinelearning:1||malicious PDF:1||malware analysis:1||math education:1||medical web forum:1||mileage interval:1||mobility sector:1||movement direction detection:1||nonexecutables:1||oneM2M platforms:1||oneM2M standards:1||online gaming retention strategies:1||overlapped latent dirichlet allocation:1||particulate matter (PM):1||peak expiratory flow rates (PEFR):1||personal exposure assessment:1||photoplethysmography:1||policy evaluation:1||portable document format:1||posting quality:1||postoperative complication:1||postoperative complications:1||pyroelectric infrared (PIR) sensor:1||realtime:1||recurrent neural network:1||sensor:1||sentiment:1||sentiment analysis:1||smart healthcare:1||smartphone:1||social activity analysis:1||social contagion:1||social network:1||spatial pyramid average pooling:1||spatial pyramid pooling:1||stacking model:1||stretch padding:1||text analysis:1||time series:1||time series forecasting:1||timeseries forecasting:1||topic model:1||transformer model:1||user behavior analysis:1||user churn prediction:1||user interaction:1||user type classification:1||vital records:1||vital sign:1||wearables:1||web forum:1||감정인식:1||객체 추적:1||객체 탐지:1||공정 검사:1||기계학습 알고리즘:1||데이터마이닝:1||딥러닝:1||머신러닝:1||머신비전:1||멀웨어 분석:1||바이트 스트림:1||보행자:1||사용자 유형 기반 분류:1||사용자 이탈 예측:1||스마트 교통안전 표지판:1||오토인코더:1||온라인 게임:1||온라인 롤플레잉 게임:1||와이어 하네스:1||운전자:1||유저 상호작용:1||유저 이탈 예측:1||유저 행위 분석:1||이미지 처리:1||이탈 사용자 예측:1||이탈 예측 모델 평가:1||인공지능:1||자동화:1||주행데이터:1||중첩된 잠재 디리클레 할당:1||5:1||토픽 모델:1||Air pollution:1||Artificial Intelligence of Things (AIoT):1||Asthma:1||Atmospheric measurements:1||Atmospheric modeling:1||Autoencoder:1||Automation:1||Behavioral sciences:1||Biological system modeling:1||Biomedical monitoring:1||Blades:1||Blood:1||Blood glucose forecasting:1||Blood pressure:1||Brain modeling:1||Byte Streams:1||Churn prediction in gaming:1||Class imbalance:1||Classification:1||Contagion:1||Controller area network (CAN):1||Convolutional neural network:1||Convolutional neural network (CNN):1||Data collection:1||Development of a prediction model forhypotension after induction of anesthesiausing machine learning:1||Diabetes:1||Diffusion:1||Disaster Tweets:1||Disaster communication:1||Disease detection:1||Disease monitoring:1||Driver:1||

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